code: def _make_tensor_datasets(self):
      train_exps = []
  
      tensor_x = torch.rand(200, 3, 28, 28)
      tensor_y = torch.randint(0, 70, (200,))
      tensor_t = torch.randint(0, 5, (200,))
      train_exps.append(
          _make_taskaware_tensor_classification_dataset(
              tensor_x, tensor_y, task_labels=tensor_t
          )
      )
  
      tensor_x = torch.rand(200, 3, 28, 28)
      tensor_y = torch.randint(0, 100, (200,))
      tensor_t = torch.randint(0, 5, (200,))
      train_exps.append(
          _make_taskaware_tensor_classification_dataset(
              tensor_x, tensor_y, task_labels=tensor_t
          )
      )
  
      test_exps = []
      test_x = torch.rand(200, 3, 28, 28)
      test_y = torch.randint(100, 200, (200,))
      test_t = torch.randint(0, 5, (200,))
      test_exps.append(
          _make_taskaware_tensor_classification_dataset(
              test_x, test_y, task_labels=test_t
          )
      )
  
      other_stream_exps = []
      other_x = torch.rand(200, 3, 28, 28)
      other_y = torch.randint(400, 600, (200,))
      other_t = torch.randint(0, 5, (200,))
      other_stream_exps.append(
          _make_taskaware_tensor_classification_dataset(
              other_x, other_y, task_labels=other_t
          )
      )
  
      return train_exps, test_exps, other_stream_exps
  
file_path: avalanche/tests/benchmarks/scenarios/deprecated/test_classification_scenario.py
imports: import unittest
  import weakref
  import gc
  import torch
  from avalanche.benchmarks import dataset_benchmark, ClassificationExperience, ClassificationScenario
  from avalanche.benchmarks.utils import _make_taskaware_tensor_classification_dataset, DataAttribute
  from torch.utils.data.dataset import TensorDataset
  from avalanche.benchmarks.utils.data import AvalancheDataset
label_desc: Use image node_id 7 for calling the ClassificationScenarioTests obj's underlying member method code with example usage: obj._make_tensor_datasets() and returns: train_exps,  test_exps,  other_stream_exps